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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Model predictive control based on urban macroscopic fundamental diagram: A city-scale routing application</title>
      <link>https://trid.trb.org/View/2653224</link>
      <description><![CDATA[The increase in motorization creates an urgent need to improve traffic congestion management techniques in urban areas. In this context, network-level control approaches are gaining prominence, and the Macroscopic Fundamental Diagram (MFD) aggregated modeling paradigm is frequently used as a fast and reliable tool to monitor city congestion levels, particularly when the city is divided into regions, each with its own MFD curve. This paper proposes and tests a hierarchical control scheme to implement a city-level Route Guidance strategy. At the upper level, Model Predictive Control (MPC) is used to determine the optimal split ratios between regions, while at the lower level, an actuation system spreads control signals to drivers by simulating Variable Message Signs on the infrastructure. The objective of this paper is to investigate and validate the robustness of this approach. The framework is tested in a complex and realistic traffic scenario representing the entire city of Luxembourg, considering various operating conditions (e.g., parameter settings, fluctuations in travel demand), behavioral factors (e.g., drivers’ compliance) and performance indicators (e.g., system effects on both controlled and uncontrolled zones). The results show that the control method effectively utilizes the network’s capacity, even with low driver compliance, and drives the entire network to the saturation regime, where optimal throughput is achieved.]]></description>
      <pubDate>Fri, 06 Feb 2026 13:52:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2653224</guid>
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    <item>
      <title>Understanding the public acceptance of automated minibuses: A market segmentation analysis across European cities</title>
      <link>https://trid.trb.org/View/2633635</link>
      <description><![CDATA[The introduction of automated vehicles (AVs) in public transport may facilitate a shift towards a more sustainable urban mobility system. However, the success of AV deployment in public transport hinges on public acceptance of this new transportation option. Acceptance levels vary significantly and are influenced more by psychographic factors—such as attitudes—than by demographic characteristics such as age or gender. To better understand the acceptance of AVs in public transport, this study attempts to analyse the diversity in the population on the basis of a psychographic market segmentation study. The study was conducted by means of a representative online survey in four European cities: Lyon, Copenhagen, Luxembourg, and Geneva. We identified five distinct market segments: unreserved goodwill, sceptical goodwill, undecided, critical reserved, and unconvinced refusers. The findings reveal substantial variations in AV acceptance among these segments, indicating that a uniform strategy is inadequate. This research provides a better understanding of the factors that influence the public's willingness to use AVs in public transport and thus reduce dependence on private vehicles. This study emphasizes that acceptance is more dependent on psychographic characteristics, particularly individual and subjective attitudes towards the associated risks and benefits.]]></description>
      <pubDate>Tue, 27 Jan 2026 16:16:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633635</guid>
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    <item>
      <title>RoboCar: A Rapidly Deployable Open Source Platform for Autonomous Driving Research</title>
      <link>https://trid.trb.org/View/2591345</link>
      <description><![CDATA[This article introduces RoboCar, an open source research platform for autonomous driving developed at the University of Luxembourg. RoboCar provides a modular cost-effective framework for the development of experimental autonomous driving systems (ADSs), utilizing the 2018 c Soul EV. The platform integrates a robust hardware and software architecture that aligns with the vehicle’s existing systems, minimizing the need for extensive modifications. It supports various autonomous driving functions and has undergone real-world testing on public roads in Luxembourg City. This article outlines the platform’s architecture, integration challenges, and initial test results, offering insights into its application in advancing autonomous driving research. RoboCar is available to anyone at https://github.com/sntubix/robocar and is released under an open source MIT license.]]></description>
      <pubDate>Fri, 24 Oct 2025 16:53:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2591345</guid>
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    <item>
      <title>Automated Vehicles as a Game Changer for Sustainable Mobility: Learnings and Solutions</title>
      <link>https://trid.trb.org/View/2579147</link>
      <description><![CDATA[This open access book explores a vision for a sustainable future in urban mobility through the AVENUE project, showcasing full-scale demonstrations of automated minibuses in European cities. AVENUE pioneers on-demand, door-to-door services, challenging traditional fixed bus itineraries. It delves into the implementation of automated vehicles, emphasizing safety, services, cybersecurity, and accessibility. Part two evaluates the economic, environmental, and social impacts on companies, citizens, and cities. By integrating automated vehicles into Mobility-as-a-Service and Intelligent Transport Systems, the book argues for the using of automated vehicles as game changer towards a transformative shift to sustainable, citizen-centric mobility. It advocates for efficiency, flexibility, and resilience of the transport system without imposing coercive transformation policies.]]></description>
      <pubDate>Fri, 24 Oct 2025 16:53:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579147</guid>
    </item>
    <item>
      <title>Technological transformations and the future of public transport labor: Imaginaries of transport administrators and workers in Luxembourg</title>
      <link>https://trid.trb.org/View/2599125</link>
      <description><![CDATA[Historically, technological change has always been a feature of public transport labor, changing the nature of work in the sector and creating new jobs while making others obsolete. Now, however, rapid developments in digitalization, automation, and electric mobility are accelerating the pace of change, raising questions about the future of work in this industry. While some of the changes are positive, potentially making transport labor safer, others pose concrete threats to transport jobs. From ticket machines to autonomous vehicles to trains that can perform many of the safety functions previously performed by onboard personnel, public transport work around the world risks being outsourced from humans to machines.In Luxembourg, where all public transport (including trains, buses, and trams) has been free at the point of use since 2020, transport administrators frequently express optimism about technological developments in the sector whereas those who work inside transport vehicles often express uncertainty about the future of their work. This paper explores how technological changes alter workers’ everyday experiences and impact how they imagine the future of their work. It engages with a rich body of anthropological literature around labor automation, work futures, and time, placing these into dialogue with ethnographic research with railway workers and public transport administrators in Luxembourg.]]></description>
      <pubDate>Tue, 07 Oct 2025 08:21:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599125</guid>
    </item>
    <item>
      <title>Exploring in-store and e-shopping against disruptive events: A cross-lagged panel SEM</title>
      <link>https://trid.trb.org/View/2550330</link>
      <description><![CDATA[This paper addresses a key gap in the literature by examining the dynamic and bidirectional relationship between in-store and e-shopping frequency during different stages of the COVID-19 pandemic. Previous studies primarily rely on cross-sectional data which fail to capture the temporal evolution and bidirectional nature of these behaviours. To overcome these limitations, this study implements a Random Intercept Cross-lagged Structural Equation Modelling (RI-CLPM) approach using three waves of panel data. Taking Luxembourg as the case study, the paper investigates the modifications in in-store shopping-related travel behaviour by evaluating shifts in trip frequency for three periods: pre-pandemic, post-peak, and relaxed measures phase. The results showed a significant shift in shopping frequency between the pre-pandemic and post-peak phase, evidencing substitution and complementarity effects both on individual as well as group level. Moreover, ANOVA and chi-square tests suggested that age and gender significantly influence in-store shopping frequency for these periods. However, no significant differences in e-shopping and in-store shopping frequencies were observed between the post-peak and the relaxed measures period. These findings provide critical insights for understanding shopping behaviour transitions and offer valuable guidance for transport policymaking. The paper closes by discussing how RI-CLPM models may improve transport policymaking, in the context of future disruptions, considering their potential for: (i) isolating policy impacts amid individual differences, (ii) addressing stable and dynamic shopping behaviours, and (iii) dealing with longitudinal data that allows for adaptive policy design.]]></description>
      <pubDate>Thu, 26 Jun 2025 11:42:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2550330</guid>
    </item>
    <item>
      <title>Exploring the influence of Internet-related perceptions and e-shopping on spatiotemporal accessibility perceptions: A study of social housing beneficiaries in Luxembourg</title>
      <link>https://trid.trb.org/View/2531112</link>
      <description><![CDATA[Perceived accessibility approaches complement objective accessibility indicators, which are beneficial for identifying accessibility-related inequalities. Current perceived accessibility studies lack in considering the space and time dimensions of accessibility, the potential impact of Internet-related perceptions, and vulnerable population groups as the center focus. This paper addresses these gaps by answering the research question:How do Internet perceptions and e-shopping frequency correlate with the perceived potential of people at housing insecurity to overcome space–time accessibility barriers with the help of the Internet? A questionnaire is first disseminated among the beneficiaries of a housing foundation in a vulnerable situation. The questionnaire asked for (i) the perceived potential to overcome space and time accessibility barriers with the help of the Internet; (ii) internet-related perceptions; (iii) actual travel behavior, and (iv) participants’ socio-economic characteristics. The data collected serves as the basis for conducting two ordinal regressions. The results show positive associations between participants’ perceived potential to overcome space and time accessibility barriers thanks to internet and their internet-related perceptions. In particular, for housing beneficiaries travelling longer distances, positive perceptions towards internet might result in a positive perceived potential to overcome both space and time accessibility barriers. From the socio-economic side, young participants are more likely to perceive that they can overcome space and time barriers thanks to the Internet, while highly-educated people only spatial barriers. The paper closes with some concluding remarks and suggests potential policy interventions.]]></description>
      <pubDate>Tue, 29 Apr 2025 16:16:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2531112</guid>
    </item>
    <item>
      <title>VeTraSPM: Novel vehicle trajectory data sequential pattern mining algorithm for link criticality analysis</title>
      <link>https://trid.trb.org/View/2476364</link>
      <description><![CDATA[This paper presents VeTraSPM (Vehicle Trajectory Data Sequential Pattern Mining), a novel algorithm designed to address the limitations of existing sequential pattern mining methods when applied to vehicle trajectory data. Current algorithms fail to capture essential characteristics such as directional flow on one-way roads (e.g., “AB” is valid but not “BA”), connectivity constraints at junctions, and the repetition of links within sequences. VeTraSPM overcomes these gaps by accurately extracting frequent patterns and confident rules while leveraging vertical projection for efficient memory and space management, enabling it to handle large datasets. Furthermore, the algorithm incorporates partitioning and parallelization techniques, further enhancing its scalability for real-world traffic environments. Three new metrics—FqMS, CMS, and SIS—are introduced to assess link criticality based on the consistent occurrence of links across movement patterns at various levels. The efficiency of VeTraSPM is demonstrated through a comparative analysis with baseline algorithms, showcasing its superior performance. The visualization of the proposed metrics offers valuable insights into link importance, supporting proactive traffic management strategies. A case study using real-world datasets from Luxembourg and Monaco validates its scalability and practical value in enhancing the resilience of urban traffic networks.]]></description>
      <pubDate>Mon, 23 Dec 2024 17:02:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2476364</guid>
    </item>
    <item>
      <title>Consumer Monitor 2023 Alternatives Fuels Observatory Country Report: Luxembourg</title>
      <link>https://trid.trb.org/View/2406643</link>
      <description><![CDATA[The European Green Deal aims for a 90% reduction of greenhouse gas emissions for transport. Different policies are in place to achieve this goal, including standards on CO₂ vehicle emissions, public procurement rules, or the recently adopted Alternative Fuels Infrastructure Regulation (AFIR). Nevertheless, in 2019, the transport sector was responsible for around one-quarter of the EU’s total CO₂ emissions, 60.6% of which were emitted by passenger cars. The passenger car is still the main transport mode and has continued to increase its share since the year 20004 . Replacing existing fleets with zero-emission vehicles is one of the key measures identified for this purpose. Important efforts have been made to promote electric cars, and therefore, identifying the main hurdles and needs of (potential) battery electric drivers can support the design and implementation of tailored strategies, policies and solutions to stimulate the demand for this type of vehicle. For more than a decade, three main barriers have been identified regarding the mass up-take of passenger battery electric vehicles (BEVs): purchase price, driving range and availability of recharging infrastructure. There have been significant advances: battery costs have dropped by 90%, vehicle range has increased from 100-150 km up to 400+ km, and the recharging infrastructure network is expanding. Nevertheless, BEVs represent only 1.68% of the total passenger cars fleet in the EU, and the recharging infrastructure coverage is still limited in some countries and urban areas. This report highlights the main findings of the 2023 EAFO Consumer Monitor survey and presents the results for Luxembourg.]]></description>
      <pubDate>Mon, 26 Aug 2024 11:19:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2406643</guid>
    </item>
    <item>
      <title>A hybrid metaheuristic to optimize electric first-mile feeder services with charging synchronization constraints and customer rejections</title>
      <link>https://trid.trb.org/View/2365108</link>
      <description><![CDATA[This paper addresses the on-demand meeting-point-based feeder electric bus routing and charging scheduling problem under charging synchronization constraints. The problem considered exhibits the structure of the location routing problem, which is more difficult to solve than many electric vehicle routing problems with capacitated charging stations. The authors propose to model the problem using a mixed-integer linear programming approach based on a layered graph structure. An efficient hybrid metaheuristic solution algorithm is proposed. A mixture of random and greedy partial charging scheduling strategies is used to find feasible charging schedules under the synchronization constraints. The algorithm is tested on instances with up to 100 customers and 49 bus stops/meeting points. The results show that the proposed algorithm provides near-optimal solutions within less one minute on average compared with the best solutions found by a mixed-integer linear programming solver set with a 4-hour computation time limit. A case study on a larger sized case with 1000 customers and 111 meeting points shows the proposed method is applicable to real-world situations.]]></description>
      <pubDate>Mon, 13 May 2024 16:32:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2365108</guid>
    </item>
    <item>
      <title>Synthetic Population: A Reliable Framework for Analysis for Agent-Based Modeling in Mobility</title>
      <link>https://trid.trb.org/View/2368128</link>
      <description><![CDATA[This paper presents a comprehensive and innovative evaluation framework for identifying a reliable population synthesis for agent-based modeling–transportation-oriented simulations (ABM–TOS). We show, via this framework and different metrics for the analysis of the generated distribution of the individuals’ attributes, that population synthesizers may fail to correctly replicate the real population heterogeneity owing to diverse control variables, data limitations, and post-simulation computation of certain parameter distributions. To show these shortcomings, the authors propose a systematic classification of different types of distributions crucial for mobility simulations. The proposed framework aims to provide a comprehensive overview of the population and serve as a rapid ’debugging’ tool to identify and rectify any flaws in a specific population during the calibration of the activity-based mobility simulation models. To prove the effectiveness of this framework, we applied it to synthetic populations generated through MOBIUS (mobility optimization based on iterative user synthesis), a newly developed synthetic population generator, which in this case was employed to create different variants of the Luxembourg population (1%, 10%, 30%). The application of our framework to these populations not only provided an effective method for assessing their goodness of fit, but also helped highlight the distributions that are most critical to the successful implementation of the methodology.]]></description>
      <pubDate>Mon, 22 Apr 2024 09:37:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2368128</guid>
    </item>
    <item>
      <title>How do workers respond to dissatisfaction with commuting and work? Insights from a panel survey in Luxembourg</title>
      <link>https://trid.trb.org/View/2350922</link>
      <description><![CDATA[Despite extensive literature on commuting satisfaction, the question of how individuals adapt to commuting dissatisfaction has not been thoroughly analysed. This study, using a Luxembourgish panel-based survey from 2013 to 2015, investigates how individuals cope with or tolerate commuting dissatisfaction over subsequent years. Employing cluster analysis, different satisfaction profiles are identified based on commuting time satisfaction (CTS) and work satisfaction (WS) in 2013. Cross-tabulations between these profiles and life events highlight that dissatisfaction predominantly leads to more frequent workplace changes than changes in residences. Logistic regression reveals that low CTS and WS combination clusters have a higher likelihood of changing workplaces in subsequent years compared to high CTS and WS combinations. Notably, the cluster with high CTS-low WS demonstrates a stronger effect on changing workplaces than the reverse combination, suggesting work dissatisfaction may outweigh dissatisfaction with commuting time. Despite these findings, a substantial majority of individuals enduring dissatisfaction are constrained from making a switch. Such findings on the prospective approaches of CTS and WS (i.e. what happens if people are dissatisfied with their commuting and work) are first of its kind and will assist in identifying the most common coping strategies individuals employ to respond to dissatisfaction in their personal lives.]]></description>
      <pubDate>Wed, 27 Mar 2024 15:40:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2350922</guid>
    </item>
    <item>
      <title>Analysis of vertical flight efficiency in European countries with extended intuitionistic fuzzy TOPSIS method</title>
      <link>https://trid.trb.org/View/2335199</link>
      <description><![CDATA[Flight efficiency is an important policy design criterion in air traffic management systems. The efficiency of flight operations becomes an important factor in identifying bottlenecks and restrictions imposed by air traffic management on the flight trajectories preferred by the airspace user. In particular, measures for fuel-efficient operations are of great interest. In this study, the vertical efficiency criteria and performances of flights in European countries are examined with the extended intuitionistic fuzzy TOPSIS method. In light of the data presented by EUROCONTROL, the weights of the vertical efficiency evaluation criteria according to their importance levels were calculated. Vertical efficiency performance values of each country were measured. In addition, a comparison of the pre-and post-pandemic periods was made. According to the results of the study, the total CO2 delta resulting from the flight level in descending and climbing was determined as the most important criterion in the vertical efficiency evaluation. In the country ranking, Luxembourg has the highest value in vertical efficiency performance in air traffic management. It is expected that the results of the research will guide decision-makers in air traffic management and contribute to the gap in the literature.]]></description>
      <pubDate>Wed, 21 Feb 2024 16:47:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2335199</guid>
    </item>
    <item>
      <title>Assessing public transport loyalty in a car-dominated society: The case of Luxembourg</title>
      <link>https://trid.trb.org/View/2248983</link>
      <description><![CDATA[Public transport (PT) systems face the challenge of retaining users and preventing a shift towards individual transport modes. While satisfaction is recognized as a key factor in user loyalty, there is a need to understand the specific PT attributes that contribute to passenger satisfaction and foster loyalty. This study aims to assess the impact of PT service attributes on user loyalty, controlling for socio-demographic characteristics. Data from an online survey conducted in the Grand Duchy of Luxembourg, a country with high car dependency, were analysed using logistic regression models. The findings highlight the importance of attributes such as reliable service, in-vehicle travel time, number of transfers, and feeling safe, while also identifying differences in attribute importance between bus and train loyalty. The study provides valuable insights for transport agencies and policymakers to enhance user loyalty and develop effective ridership retention strategies. These findings are particularly relevant in the post-pandemic scenario and can contribute to addressing car dependency challenges in diverse metropolitan areas. The paper concludes with policy recommendations to improve PT services based on the identified attributes.]]></description>
      <pubDate>Mon, 25 Sep 2023 14:10:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2248983</guid>
    </item>
    <item>
      <title>Introducing Automated Shuttles in the Public Transport of European Cities: The Case of the AVENUE Project</title>
      <link>https://trid.trb.org/View/1973116</link>
      <description><![CDATA[The current mobility paradigm has reached a tipping point. Individual mobility, based on cheap fossil fuel and high CO₂ emissions no longer meet the needs posed by a globally increasing demand for passenger mobility, neither corresponds to the climate agenda. In this regard, innovations and technologies play an important role to shape the future mobility and provide solutions for more efficient, affordable, accessible, and sustainable mobility in cities. This paper aims to explore how innovations on mobility, such as shared automated electric vehicles (SAEV) can contribute to a positive change in the mobility paradigm and sustainable mobility, and to this end, which are the current obstacles to be overcome and the key factors related to SAEV’s deployment. Thereby, it presents the case of the Autonomous Vehicles to Evolve to a New Urban Experience - ‘AVENUE’, a European project that has implemented pilot trials to test automated shuttles within the public transport of Lyon, Geneva, Luxembourg, and Copenhagen. Based on primary data from the project and secondary data from AVENUE public reports, the study reports on the project implementation in the four cities and first learnings through obstacles and key factors to accelerate the deployment of automated shuttles in cities. It contributes to the discussion on technical & operational, social, and legal obstacles as well as key elements in the deployment of automated shuttles.]]></description>
      <pubDate>Wed, 22 Feb 2023 17:16:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973116</guid>
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